What you'll learn
Data engineering concepts and AWS services
Fetching data from external Rest Api
Fetching data from SFTP server
Ingesting data into a Database
Creating Serverless Data Lake using S3 and Athena
Creating Glue ETL jobs and Workflows
Transforming data into Parquet format
Learn how to store data in S3 Data lakes using Parquet columnar file formats
Requirements
Hands on expertise on Python & Sql is a must
An active AWS account
Description
A hands on course that covers majority of the typical data engineering / ETL scenarios. In this course you will learn:Different services and concepts of AWS data engineeringCreating serverless data lake using S3, Glue and AthenaIngesting data using Rest ApiIngesting data using Sftp serverIngesting data into Database (AWS RDS - Postgre SQL)Incremental data loadingPrerequisites:An active AWS accountPython / SQL knowledge
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Data Engineering Services
Lecture 2 S3
Lecture 3 Athena
Lecture 4 Glue
Lecture 5 Lambda
Lecture 6 RDS
Lecture 7 SQS
Lecture 8 SNS
Lecture 9 Kinesis
Section 3: Live Demos
Lecture 10 Serverless Datawarehousing
Lecture 11 Ingest data from a Rest Api
Lecture 12 Ingest data into a SQL database (Postgre SQL)
Lecture 13 Incremental data Loading
Lecture 14 Ingest data from a SFTP server
Beginner python developers curious for data science,Data engineers,BI/ ETL Developers,Data Scientists / Analysts,Anyone from technical background who wants to learn Data engineering in AWS,Software developers who want to learn different ways to ingest data into AWS and build a datawarehouse

Homepage

https://www.udemy.com/course/learn-aws-data-engineering/

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